Jiazhi Guan*, Zhanwang Zhang*, Hang Zhou†, Tianshu Hu†, Kaisiyuan Wang, Dongliang He, Haocheng Feng, Jingtuo Liu, Errui Ding, Ziwei Liu, Jingdong Wang

We propose StyleSync, an effective framework that enables high-fidelity lip synchronization. We identify that a style-based generator would sufficiently enable such a charming property on both one-shot and few-shot scenarios.

Inference script and model code have been released.

The decision to suspend the release of the model weights has been made by our team based on various considerations. At present, I also do not have a specific expected date for its release. However, if you are interested in utilizing our demo for academic purposes, such as conducting a comparison in your paper, please don't hesitate to contact me by [guanjz20 at mails dot tsinghua dot edu dot cn].

@inproceedings{guan2023stylesync,
  title = {StyleSync: High-Fidelity Generalized and Personalized Lip Sync in Style-based Generator},
  author = {Guan, Jiazhi and Zhang, Zhanwang and Zhou, Hang and HU, Tianshu and Wang, Kaisiyuan and He, Dongliang and Feng, Haocheng and Liu, Jingtuo and Ding, Errui and Liu, Ziwei and Wang, Jingdong},
  booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2023}
}